Overview

Brought to you by YData

Dataset statistics

Number of variables21
Number of observations6178
Missing cells10788
Missing cells (%)8.3%
Duplicate rows4
Duplicate rows (%)0.1%
Total size in memory7.7 MiB
Average record size in memory1.3 KiB

Variable types

Text3
Numeric6
Categorical9
Unsupported2
DateTime1

Alerts

Dataset has 4 (0.1%) duplicate rowsDuplicates
class_auto is highly imbalanced (81.4%)Imbalance
state is highly imbalanced (53.4%)Imbalance
door is highly imbalanced (82.1%)Imbalance
volume has 379 (6.1%) missing valuesMissing
tip_dvigatelja has 222 (3.6%) missing valuesMissing
class_auto has 639 (10.3%) missing valuesMissing
body has 689 (11.2%) missing valuesMissing
state has 541 (8.8%) missing valuesMissing
door has 787 (12.7%) missing valuesMissing
fuel has 530 (8.6%) missing valuesMissing
transmission has 394 (6.4%) missing valuesMissing
conditioner has 1056 (17.1%) missing valuesMissing
audio has 1634 (26.4%) missing valuesMissing
mileage has 2944 (47.7%) missing valuesMissing
mileage_orig has 973 (15.7%) missing valuesMissing
fone is an unsupported type, check if it needs cleaning or further analysisUnsupported
manth is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2025-02-16 12:03:05.367880
Analysis finished2025-02-16 12:03:19.302939
Duration13.94 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

brend
Text

Distinct62
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size436.1 KiB
2025-02-16T15:03:19.749141image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length6.7507284
Min length3

Characters and Unicode

Total characters41706
Distinct characters56
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)0.1%

Sample

1st rowToyota
2nd rowVolkswagen
3rd rowToyota
4th rowBMW
5th rowLexus
ValueCountFrequency (%)
toyota 910
14.7%
volkswagen 854
13.8%
mercedes-benz 651
10.5%
lexus 498
 
8.1%
bmw 430
 
7.0%
ford 333
 
5.4%
audi 299
 
4.8%
opel 247
 
4.0%
nissan 217
 
3.5%
honda 194
 
3.1%
Other values (52) 1545
25.0%
2025-02-16T15:03:20.655996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 4841
 
11.6%
o 3681
 
8.8%
a 3146
 
7.5%
s 2911
 
7.0%
n 2417
 
5.8%
d 1898
 
4.6%
i 1559
 
3.7%
l 1517
 
3.6%
t 1459
 
3.5%
M 1443
 
3.5%
Other values (46) 16834
40.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33041
79.2%
Uppercase Letter 8014
 
19.2%
Dash Punctuation 651
 
1.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 1443
18.0%
B 1083
13.5%
T 1001
12.5%
V 928
11.6%
L 552
 
6.9%
W 430
 
5.4%
A 364
 
4.5%
F 356
 
4.4%
H 344
 
4.3%
O 247
 
3.1%
Other values (19) 1266
15.8%
Lowercase Letter
ValueCountFrequency (%)
e 4841
14.7%
o 3681
11.1%
a 3146
 
9.5%
s 2911
 
8.8%
n 2417
 
7.3%
d 1898
 
5.7%
i 1559
 
4.7%
l 1517
 
4.6%
t 1459
 
4.4%
u 1350
 
4.1%
Other values (16) 8262
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 651
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40773
97.8%
Common 651
 
1.6%
Cyrillic 282
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4841
 
11.9%
o 3681
 
9.0%
a 3146
 
7.7%
s 2911
 
7.1%
n 2417
 
5.9%
d 1898
 
4.7%
i 1559
 
3.8%
l 1517
 
3.7%
t 1459
 
3.6%
M 1443
 
3.5%
Other values (35) 15901
39.0%
Cyrillic
ValueCountFrequency (%)
З 93
33.0%
А 90
31.9%
В 50
17.7%
Г 35
 
12.4%
У 4
 
1.4%
И 2
 
0.7%
Л 2
 
0.7%
М 2
 
0.7%
а 2
 
0.7%
з 2
 
0.7%
Common
ValueCountFrequency (%)
- 651
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41424
99.3%
Cyrillic 282
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4841
 
11.7%
o 3681
 
8.9%
a 3146
 
7.6%
s 2911
 
7.0%
n 2417
 
5.8%
d 1898
 
4.6%
i 1559
 
3.8%
l 1517
 
3.7%
t 1459
 
3.5%
M 1443
 
3.5%
Other values (36) 16552
40.0%
Cyrillic
ValueCountFrequency (%)
З 93
33.0%
А 90
31.9%
В 50
17.7%
Г 35
 
12.4%
У 4
 
1.4%
И 2
 
0.7%
Л 2
 
0.7%
М 2
 
0.7%
а 2
 
0.7%
з 2
 
0.7%

volume
Real number (ℝ)

MISSING 

Distinct248
Distinct (%)4.3%
Missing379
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean2270.9895
Minimum1000
Maximum7600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-02-16T15:03:20.998076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1400
Q11800
median2000
Q32500
95-th percentile3500
Maximum7600
Range6600
Interquartile range (IQR)700

Descriptive statistics

Standard deviation717.38549
Coefficient of variation (CV)0.31589116
Kurtosis3.8125062
Mean2270.9895
Median Absolute Deviation (MAD)400
Skewness1.4960778
Sum13169468
Variance514641.94
MonotonicityNot monotonic
2025-02-16T15:03:21.395166image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 1312
21.2%
2500 453
 
7.3%
1800 443
 
7.2%
2200 387
 
6.3%
3000 344
 
5.6%
3500 330
 
5.3%
1600 327
 
5.3%
1900 243
 
3.9%
2400 225
 
3.6%
1500 201
 
3.3%
Other values (238) 1534
24.8%
(Missing) 379
 
6.1%
ValueCountFrequency (%)
1000 81
1.3%
1098 1
 
< 0.1%
1100 6
 
0.1%
1198 1
 
< 0.1%
1200 19
 
0.3%
1230 1
 
< 0.1%
1246 2
 
< 0.1%
1250 1
 
< 0.1%
1300 46
0.7%
1323 1
 
< 0.1%
ValueCountFrequency (%)
7600 1
 
< 0.1%
6700 1
 
< 0.1%
6100 1
 
< 0.1%
6000 5
 
0.1%
5900 1
 
< 0.1%
5700 15
0.2%
5600 3
 
< 0.1%
5599 1
 
< 0.1%
5500 4
 
0.1%
5496 1
 
< 0.1%

tip_dvigatelja
Categorical

MISSING 

Distinct5
Distinct (%)0.1%
Missing222
Missing (%)3.6%
Memory size703.0 KiB
Дизель
2229 
Бензин
1431 
Бензин-Газ
1229 
Гибрид
945 
Электро
 
122

Length

Max length10
Median length6
Mean length6.8458697
Min length6

Characters and Unicode

Total characters40774
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowДизель
2nd rowБензин-Газ
3rd rowГибрид
4th rowБензин
5th rowБензин

Common Values

ValueCountFrequency (%)
Дизель 2229
36.1%
Бензин 1431
23.2%
Бензин-Газ 1229
19.9%
Гибрид 945
15.3%
Электро 122
 
2.0%
(Missing) 222
 
3.6%

Length

2025-02-16T15:03:21.791252image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:22.128363image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
дизель 2229
37.4%
бензин 1431
24.0%
бензин-газ 1229
20.6%
гибрид 945
15.9%
электро 122
 
2.0%

Most occurring characters

ValueCountFrequency (%)
и 6779
16.6%
з 6118
15.0%
н 5320
13.0%
е 5011
12.3%
Б 2660
 
6.5%
л 2351
 
5.8%
Д 2229
 
5.5%
ь 2229
 
5.5%
Г 2174
 
5.3%
- 1229
 
3.0%
Other values (8) 4674
11.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32360
79.4%
Uppercase Letter 7185
 
17.6%
Dash Punctuation 1229
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
и 6779
20.9%
з 6118
18.9%
н 5320
16.4%
е 5011
15.5%
л 2351
 
7.3%
ь 2229
 
6.9%
а 1229
 
3.8%
р 1067
 
3.3%
б 945
 
2.9%
д 945
 
2.9%
Other values (3) 366
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
Б 2660
37.0%
Д 2229
31.0%
Г 2174
30.3%
Э 122
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1229
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 39545
97.0%
Common 1229
 
3.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
и 6779
17.1%
з 6118
15.5%
н 5320
13.5%
е 5011
12.7%
Б 2660
 
6.7%
л 2351
 
5.9%
Д 2229
 
5.6%
ь 2229
 
5.6%
Г 2174
 
5.5%
а 1229
 
3.1%
Other values (7) 3445
8.7%
Common
ValueCountFrequency (%)
- 1229
100.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 39545
97.0%
ASCII 1229
 
3.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
и 6779
17.1%
з 6118
15.5%
н 5320
13.5%
е 5011
12.7%
Б 2660
 
6.7%
л 2351
 
5.9%
Д 2229
 
5.6%
ь 2229
 
5.6%
Г 2174
 
5.5%
а 1229
 
3.1%
Other values (7) 3445
8.7%
ASCII
ValueCountFrequency (%)
- 1229
100.0%

god
Real number (ℝ)

Distinct48
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2005.5388
Minimum1958
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-02-16T15:03:22.473513image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1958
5-th percentile1992
Q12001
median2006
Q32012
95-th percentile2017
Maximum2019
Range61
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.5144583
Coefficient of variation (CV)0.0037468525
Kurtosis0.2312292
Mean2005.5388
Median Absolute Deviation (MAD)5
Skewness-0.43606698
Sum12390219
Variance56.467084
MonotonicityNot monotonic
2025-02-16T15:03:22.849597image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
2006 394
 
6.4%
2005 364
 
5.9%
2007 357
 
5.8%
2008 346
 
5.6%
2013 343
 
5.6%
2004 325
 
5.3%
2003 298
 
4.8%
2000 257
 
4.2%
2014 253
 
4.1%
2001 251
 
4.1%
Other values (38) 2990
48.4%
ValueCountFrequency (%)
1958 1
 
< 0.1%
1966 1
 
< 0.1%
1967 1
 
< 0.1%
1973 1
 
< 0.1%
1975 1
 
< 0.1%
1977 1
 
< 0.1%
1978 1
 
< 0.1%
1979 2
 
< 0.1%
1980 7
0.1%
1981 3
< 0.1%
ValueCountFrequency (%)
2019 103
 
1.7%
2018 153
2.5%
2017 151
2.4%
2016 161
2.6%
2015 176
2.8%
2014 253
4.1%
2013 343
5.6%
2012 230
3.7%
2011 177
2.9%
2010 184
3.0%

prise
Real number (ℝ)

Distinct610
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7627.6949
Minimum1000
Maximum380000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-02-16T15:03:23.228680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1350
Q12800
median5500
Q310200
95-th percentile20000
Maximum380000
Range379000
Interquartile range (IQR)7400

Descriptive statistics

Standard deviation8247.0025
Coefficient of variation (CV)1.081192
Kurtosis680.10256
Mean7627.6949
Median Absolute Deviation (MAD)3200
Skewness16.372686
Sum47123899
Variance68013050
MonotonicityNot monotonic
2025-02-16T15:03:23.611770image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 141
 
2.3%
2500 136
 
2.2%
3500 133
 
2.2%
4500 121
 
2.0%
1500 105
 
1.7%
3000 93
 
1.5%
5000 89
 
1.4%
1700 87
 
1.4%
5500 84
 
1.4%
2700 84
 
1.4%
Other values (600) 5105
82.6%
ValueCountFrequency (%)
1000 82
1.3%
1001 1
 
< 0.1%
1050 3
 
< 0.1%
1100 48
0.8%
1111 9
 
0.1%
1150 14
 
0.2%
1199 1
 
< 0.1%
1200 79
1.3%
1234 1
 
< 0.1%
1250 27
 
0.4%
ValueCountFrequency (%)
380000 1
< 0.1%
100500 1
< 0.1%
99999 1
< 0.1%
91200 1
< 0.1%
55000 2
< 0.1%
44750 1
< 0.1%
42500 1
< 0.1%
42000 2
< 0.1%
40000 1
< 0.1%
39900 1
< 0.1%

class_auto
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing639
Missing (%)10.3%
Memory size710.3 KiB
Легковой
5382 
Грузовой
 
157

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters44312
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowЛегковой
2nd rowЛегковой
3rd rowЛегковой
4th rowЛегковой
5th rowЛегковой

Common Values

ValueCountFrequency (%)
Легковой 5382
87.1%
Грузовой 157
 
2.5%
(Missing) 639
 
10.3%

Length

2025-02-16T15:03:23.973886image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:24.217941image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
легковой 5382
97.2%
грузовой 157
 
2.8%

Most occurring characters

ValueCountFrequency (%)
о 11078
25.0%
в 5539
12.5%
й 5539
12.5%
Л 5382
12.1%
е 5382
12.1%
г 5382
12.1%
к 5382
12.1%
Г 157
 
0.4%
р 157
 
0.4%
у 157
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38773
87.5%
Uppercase Letter 5539
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 11078
28.6%
в 5539
14.3%
й 5539
14.3%
е 5382
13.9%
г 5382
13.9%
к 5382
13.9%
р 157
 
0.4%
у 157
 
0.4%
з 157
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
Л 5382
97.2%
Г 157
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 44312
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 11078
25.0%
в 5539
12.5%
й 5539
12.5%
Л 5382
12.1%
е 5382
12.1%
г 5382
12.1%
к 5382
12.1%
Г 157
 
0.4%
р 157
 
0.4%
у 157
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 44312
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 11078
25.0%
в 5539
12.5%
й 5539
12.5%
Л 5382
12.1%
е 5382
12.1%
г 5382
12.1%
к 5382
12.1%
Г 157
 
0.4%
р 157
 
0.4%
у 157
 
0.4%

body
Categorical

MISSING 

Distinct14
Distinct (%)0.3%
Missing689
Missing (%)11.2%
Memory size695.1 KiB
седан
1816 
универсал
918 
внедорожник
706 
хетчбек
656 
минивен
601 
Other values (9)
792 

Length

Max length12
Median length11
Mean length7.4093642
Min length4

Characters and Unicode

Total characters40670
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowуниверсал
2nd rowминивен
3rd rowхетчбек
4th rowвнедорожник
5th rowхетчбек

Common Values

ValueCountFrequency (%)
седан 1816
29.4%
универсал 918
14.9%
внедорожник 706
 
11.4%
хетчбек 656
 
10.6%
минивен 601
 
9.7%
кроссовер 449
 
7.3%
грузовой 95
 
1.5%
микроавтобус 85
 
1.4%
купе 56
 
0.9%
фургон 49
 
0.8%
Other values (4) 58
 
0.9%
(Missing) 689
 
11.2%

Length

2025-02-16T15:03:24.537015image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
седан 1816
33.1%
универсал 918
16.7%
внедорожник 706
 
12.9%
хетчбек 656
 
12.0%
минивен 601
 
10.9%
кроссовер 449
 
8.2%
грузовой 95
 
1.7%
микроавтобус 85
 
1.5%
купе 56
 
1.0%
фургон 49
 
0.9%
Other values (4) 58
 
1.1%

Most occurring characters

ValueCountFrequency (%)
е 5871
14.4%
н 5429
13.3%
с 3726
9.2%
и 2992
7.4%
в 2863
7.0%
а 2845
7.0%
р 2764
 
6.8%
о 2741
 
6.7%
д 2522
 
6.2%
к 1969
 
4.8%
Other values (13) 6948
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40670
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
е 5871
14.4%
н 5429
13.3%
с 3726
9.2%
и 2992
7.4%
в 2863
7.0%
а 2845
7.0%
р 2764
 
6.8%
о 2741
 
6.7%
д 2522
 
6.2%
к 1969
 
4.8%
Other values (13) 6948
17.1%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 40670
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
е 5871
14.4%
н 5429
13.3%
с 3726
9.2%
и 2992
7.4%
в 2863
7.0%
а 2845
7.0%
р 2764
 
6.8%
о 2741
 
6.7%
д 2522
 
6.2%
к 1969
 
4.8%
Other values (13) 6948
17.1%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 40670
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
е 5871
14.4%
н 5429
13.3%
с 3726
9.2%
и 2992
7.4%
в 2863
7.0%
а 2845
7.0%
р 2764
 
6.8%
о 2741
 
6.7%
д 2522
 
6.2%
к 1969
 
4.8%
Other values (13) 6948
17.1%

state
Categorical

IMBALANCE  MISSING 

Distinct6
Distinct (%)0.1%
Missing541
Missing (%)8.8%
Memory size711.8 KiB
Отличное
3317 
Хорошее
2105 
Удовлетворительное
 
143
Новый
 
62
Битыйавто
 
9

Length

Max length18
Median length8
Mean length7.848501
Min length5

Characters and Unicode

Total characters44242
Distinct characters22
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowОтличное
2nd rowОтличное
3rd rowОтличное
4th rowХорошее
5th rowОтличное

Common Values

ValueCountFrequency (%)
Отличное 3317
53.7%
Хорошее 2105
34.1%
Удовлетворительное 143
 
2.3%
Новый 62
 
1.0%
Битыйавто 9
 
0.1%
Плохое 1
 
< 0.1%
(Missing) 541
 
8.8%

Length

2025-02-16T15:03:24.881110image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:25.174590image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
отличное 3317
58.8%
хорошее 2105
37.3%
удовлетворительное 143
 
2.5%
новый 62
 
1.1%
битыйавто 9
 
0.2%
плохое 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
о 8029
18.1%
е 7957
18.0%
т 3621
8.2%
л 3604
8.1%
и 3469
7.8%
н 3460
7.8%
О 3317
7.5%
ч 3317
7.5%
р 2248
 
5.1%
Х 2105
 
4.8%
Other values (12) 3115
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38605
87.3%
Uppercase Letter 5637
 
12.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 8029
20.8%
е 7957
20.6%
т 3621
9.4%
л 3604
9.3%
и 3469
9.0%
н 3460
9.0%
ч 3317
8.6%
р 2248
 
5.8%
ш 2105
 
5.5%
в 357
 
0.9%
Other values (6) 438
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
О 3317
58.8%
Х 2105
37.3%
У 143
 
2.5%
Н 62
 
1.1%
Б 9
 
0.2%
П 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 44242
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 8029
18.1%
е 7957
18.0%
т 3621
8.2%
л 3604
8.1%
и 3469
7.8%
н 3460
7.8%
О 3317
7.5%
ч 3317
7.5%
р 2248
 
5.1%
Х 2105
 
4.8%
Other values (12) 3115
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 44242
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 8029
18.1%
е 7957
18.0%
т 3621
8.2%
л 3604
8.1%
и 3469
7.8%
н 3460
7.8%
О 3317
7.5%
ч 3317
7.5%
р 2248
 
5.1%
Х 2105
 
4.8%
Other values (12) 3115
 
7.0%

door
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)0.1%
Missing787
Missing (%)12.7%
Memory size413.3 KiB
4/5
5156 
2/3
 
204
6/7
 
31

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters16173
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4/5
2nd row4/5
3rd row4/5
4th row4/5
5th row4/5

Common Values

ValueCountFrequency (%)
4/5 5156
83.5%
2/3 204
 
3.3%
6/7 31
 
0.5%
(Missing) 787
 
12.7%

Length

2025-02-16T15:03:25.522667image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:25.805210image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
4/5 5156
95.6%
2/3 204
 
3.8%
6/7 31
 
0.6%

Most occurring characters

ValueCountFrequency (%)
/ 5391
33.3%
4 5156
31.9%
5 5156
31.9%
2 204
 
1.3%
3 204
 
1.3%
6 31
 
0.2%
7 31
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10782
66.7%
Other Punctuation 5391
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 5156
47.8%
5 5156
47.8%
2 204
 
1.9%
3 204
 
1.9%
6 31
 
0.3%
7 31
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 5391
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16173
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 5391
33.3%
4 5156
31.9%
5 5156
31.9%
2 204
 
1.3%
3 204
 
1.3%
6 31
 
0.2%
7 31
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 5391
33.3%
4 5156
31.9%
5 5156
31.9%
2 204
 
1.3%
3 204
 
1.3%
6 31
 
0.2%
7 31
 
0.2%

fuel
Categorical

MISSING 

Distinct4
Distinct (%)0.1%
Missing530
Missing (%)8.6%
Memory size662.9 KiB
бензин
2469 
дизель
2178 
газ
803 
электро
 
198

Length

Max length7
Median length6
Mean length5.608534
Min length3

Characters and Unicode

Total characters31677
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowдизель
2nd rowбензин
3rd rowбензин
4th rowдизель
5th rowбензин

Common Values

ValueCountFrequency (%)
бензин 2469
40.0%
дизель 2178
35.3%
газ 803
 
13.0%
электро 198
 
3.2%
(Missing) 530
 
8.6%

Length

2025-02-16T15:03:26.134287image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:26.436404image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
бензин 2469
43.7%
дизель 2178
38.6%
газ 803
 
14.2%
электро 198
 
3.5%

Most occurring characters

ValueCountFrequency (%)
з 5450
17.2%
н 4938
15.6%
е 4845
15.3%
и 4647
14.7%
б 2469
7.8%
л 2376
7.5%
д 2178
 
6.9%
ь 2178
 
6.9%
г 803
 
2.5%
а 803
 
2.5%
Other values (5) 990
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31677
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
з 5450
17.2%
н 4938
15.6%
е 4845
15.3%
и 4647
14.7%
б 2469
7.8%
л 2376
7.5%
д 2178
 
6.9%
ь 2178
 
6.9%
г 803
 
2.5%
а 803
 
2.5%
Other values (5) 990
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 31677
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
з 5450
17.2%
н 4938
15.6%
е 4845
15.3%
и 4647
14.7%
б 2469
7.8%
л 2376
7.5%
д 2178
 
6.9%
ь 2178
 
6.9%
г 803
 
2.5%
а 803
 
2.5%
Other values (5) 990
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 31677
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
з 5450
17.2%
н 4938
15.6%
е 4845
15.3%
и 4647
14.7%
б 2469
7.8%
л 2376
7.5%
д 2178
 
6.9%
ь 2178
 
6.9%
г 803
 
2.5%
а 803
 
2.5%
Other values (5) 990
 
3.1%

transmission
Categorical

MISSING 

Distinct6
Distinct (%)0.1%
Missing394
Missing (%)6.4%
Memory size757.4 KiB
автомат
2861 
5-тиступ.мех.
2039 
6-тиступ.мех.
783 
4-ёхступ.мех.
 
49
роботизированая
 
43

Length

Max length15
Median length13
Mean length10.043914
Min length7

Characters and Unicode

Total characters58094
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6-тиступ.мех.
2nd row5-тиступ.мех.
3rd rowавтомат
4th row5-тиступ.мех.
5th rowавтомат

Common Values

ValueCountFrequency (%)
автомат 2861
46.3%
5-тиступ.мех. 2039
33.0%
6-тиступ.мех. 783
 
12.7%
4-ёхступ.мех. 49
 
0.8%
роботизированая 43
 
0.7%
полуавтомат 9
 
0.1%
(Missing) 394
 
6.4%

Length

2025-02-16T15:03:26.754474image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:27.078779image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
автомат 2861
49.5%
5-тиступ.мех 2039
35.3%
6-тиступ.мех 783
 
13.5%
4-ёхступ.мех 49
 
0.8%
роботизированая 43
 
0.7%
полуавтомат 9
 
0.2%

Most occurring characters

ValueCountFrequency (%)
т 11476
19.8%
а 5826
10.0%
. 5742
9.9%
м 5741
9.9%
о 3008
 
5.2%
х 2920
 
5.0%
в 2913
 
5.0%
и 2908
 
5.0%
у 2880
 
5.0%
п 2880
 
5.0%
Other values (13) 11800
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46610
80.2%
Other Punctuation 5742
 
9.9%
Dash Punctuation 2871
 
4.9%
Decimal Number 2871
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
т 11476
24.6%
а 5826
12.5%
м 5741
12.3%
о 3008
 
6.5%
х 2920
 
6.3%
в 2913
 
6.2%
и 2908
 
6.2%
у 2880
 
6.2%
п 2880
 
6.2%
с 2871
 
6.2%
Other values (8) 3187
 
6.8%
Decimal Number
ValueCountFrequency (%)
5 2039
71.0%
6 783
 
27.3%
4 49
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 5742
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2871
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 46610
80.2%
Common 11484
 
19.8%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
т 11476
24.6%
а 5826
12.5%
м 5741
12.3%
о 3008
 
6.5%
х 2920
 
6.3%
в 2913
 
6.2%
и 2908
 
6.2%
у 2880
 
6.2%
п 2880
 
6.2%
с 2871
 
6.2%
Other values (8) 3187
 
6.8%
Common
ValueCountFrequency (%)
. 5742
50.0%
- 2871
25.0%
5 2039
 
17.8%
6 783
 
6.8%
4 49
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 46610
80.2%
ASCII 11484
 
19.8%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
т 11476
24.6%
а 5826
12.5%
м 5741
12.3%
о 3008
 
6.5%
х 2920
 
6.3%
в 2913
 
6.2%
и 2908
 
6.2%
у 2880
 
6.2%
п 2880
 
6.2%
с 2871
 
6.2%
Other values (8) 3187
 
6.8%
ASCII
ValueCountFrequency (%)
. 5742
50.0%
- 2871
25.0%
5 2039
 
17.8%
6 783
 
6.8%
4 49
 
0.4%

conditioner
Categorical

MISSING 

Distinct3
Distinct (%)0.1%
Missing1056
Missing (%)17.1%
Memory size793.5 KiB
климатконтроль
3228 
кондиционер
1499 
безкондиционера
395 

Length

Max length15
Median length14
Mean length13.199141
Min length11

Characters and Unicode

Total characters67606
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowклиматконтроль
2nd rowклиматконтроль
3rd rowклиматконтроль
4th rowклиматконтроль
5th rowклиматконтроль

Common Values

ValueCountFrequency (%)
климатконтроль 3228
52.2%
кондиционер 1499
24.3%
безкондиционера 395
 
6.4%
(Missing) 1056
 
17.1%

Length

2025-02-16T15:03:27.476866image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:27.820961image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
климатконтроль 3228
63.0%
кондиционер 1499
29.3%
безкондиционера 395
 
7.7%

Most occurring characters

ValueCountFrequency (%)
о 10244
15.2%
к 8350
12.4%
и 7016
10.4%
н 7016
10.4%
л 6456
9.5%
т 6456
9.5%
р 5122
7.6%
а 3623
 
5.4%
м 3228
 
4.8%
ь 3228
 
4.8%
Other values (5) 6867
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 67606
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
о 10244
15.2%
к 8350
12.4%
и 7016
10.4%
н 7016
10.4%
л 6456
9.5%
т 6456
9.5%
р 5122
7.6%
а 3623
 
5.4%
м 3228
 
4.8%
ь 3228
 
4.8%
Other values (5) 6867
10.2%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 67606
100.0%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
о 10244
15.2%
к 8350
12.4%
и 7016
10.4%
н 7016
10.4%
л 6456
9.5%
т 6456
9.5%
р 5122
7.6%
а 3623
 
5.4%
м 3228
 
4.8%
ь 3228
 
4.8%
Other values (5) 6867
10.2%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 67606
100.0%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
о 10244
15.2%
к 8350
12.4%
и 7016
10.4%
н 7016
10.4%
л 6456
9.5%
т 6456
9.5%
р 5122
7.6%
а 3623
 
5.4%
м 3228
 
4.8%
ь 3228
 
4.8%
Other values (5) 6867
10.2%

audio
Categorical

MISSING 

Distinct4
Distinct (%)0.1%
Missing1634
Missing (%)26.4%
Memory size947.8 KiB
автомагнитолаCD/MP3(сUSBиBluetooth)
2351 
автомагнитола
1036 
автомагнитолаCD/MP3(безUSB)
830 
автомагнитолаHi-End
327 

Length

Max length35
Median length35
Mean length27.371479
Min length13

Characters and Unicode

Total characters124376
Distinct characters36
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowавтомагнитолаCD/MP3(сUSBиBluetooth)
2nd rowавтомагнитолаCD/MP3(безUSB)
3rd rowавтомагнитолаCD/MP3(сUSBиBluetooth)
4th rowавтомагнитолаCD/MP3(безUSB)
5th rowавтомагнитолаCD/MP3(безUSB)

Common Values

ValueCountFrequency (%)
автомагнитолаCD/MP3(сUSBиBluetooth) 2351
38.1%
автомагнитола 1036
16.8%
автомагнитолаCD/MP3(безUSB) 830
 
13.4%
автомагнитолаHi-End 327
 
5.3%
(Missing) 1634
26.4%

Length

2025-02-16T15:03:28.134044image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-16T15:03:28.679181image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
автомагнитолаcd/mp3(сusbиbluetooth 2351
51.7%
автомагнитола 1036
22.8%
автомагнитолаcd/mp3(безusb 830
 
18.3%
автомагнитолаhi-end 327
 
7.2%

Most occurring characters

ValueCountFrequency (%)
а 13632
 
11.0%
т 9088
 
7.3%
о 9088
 
7.3%
и 6895
 
5.5%
B 5532
 
4.4%
o 4702
 
3.8%
t 4702
 
3.8%
м 4544
 
3.7%
г 4544
 
3.7%
н 4544
 
3.7%
Other values (26) 57105
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 86053
69.2%
Uppercase Letter 25272
 
20.3%
Open Punctuation 3181
 
2.6%
Close Punctuation 3181
 
2.6%
Other Punctuation 3181
 
2.6%
Decimal Number 3181
 
2.6%
Dash Punctuation 327
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
а 13632
15.8%
т 9088
10.6%
о 9088
10.6%
и 6895
 
8.0%
o 4702
 
5.5%
t 4702
 
5.5%
м 4544
 
5.3%
г 4544
 
5.3%
н 4544
 
5.3%
л 4544
 
5.3%
Other values (12) 19770
23.0%
Uppercase Letter
ValueCountFrequency (%)
B 5532
21.9%
U 3181
12.6%
S 3181
12.6%
C 3181
12.6%
P 3181
12.6%
M 3181
12.6%
D 3181
12.6%
H 327
 
1.3%
E 327
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 3181
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3181
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3181
100.0%
Decimal Number
ValueCountFrequency (%)
3 3181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 327
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 66264
53.3%
Latin 45061
36.2%
Common 13051
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 5532
12.3%
o 4702
10.4%
t 4702
10.4%
U 3181
 
7.1%
S 3181
 
7.1%
C 3181
 
7.1%
P 3181
 
7.1%
M 3181
 
7.1%
D 3181
 
7.1%
h 2351
 
5.2%
Other values (8) 8688
19.3%
Cyrillic
ValueCountFrequency (%)
а 13632
20.6%
т 9088
13.7%
о 9088
13.7%
и 6895
10.4%
м 4544
 
6.9%
г 4544
 
6.9%
н 4544
 
6.9%
л 4544
 
6.9%
в 4544
 
6.9%
с 2351
 
3.5%
Other values (3) 2490
 
3.8%
Common
ValueCountFrequency (%)
( 3181
24.4%
) 3181
24.4%
/ 3181
24.4%
3 3181
24.4%
- 327
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 66264
53.3%
ASCII 58112
46.7%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
а 13632
20.6%
т 9088
13.7%
о 9088
13.7%
и 6895
10.4%
м 4544
 
6.9%
г 4544
 
6.9%
н 4544
 
6.9%
л 4544
 
6.9%
в 4544
 
6.9%
с 2351
 
3.5%
Other values (3) 2490
 
3.8%
ASCII
ValueCountFrequency (%)
B 5532
 
9.5%
o 4702
 
8.1%
t 4702
 
8.1%
( 3181
 
5.5%
) 3181
 
5.5%
U 3181
 
5.5%
S 3181
 
5.5%
C 3181
 
5.5%
/ 3181
 
5.5%
P 3181
 
5.5%
Other values (13) 20909
36.0%

mileage
Real number (ℝ)

MISSING 

Distinct669
Distinct (%)20.7%
Missing2944
Missing (%)47.7%
Infinite0
Infinite (%)0.0%
Mean225974.12
Minimum11000
Maximum1000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-02-16T15:03:29.040298image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile79000
Q1154000
median220000
Q3290000
95-th percentile390000
Maximum1000000
Range989000
Interquartile range (IQR)136000

Descriptive statistics

Standard deviation101923.99
Coefficient of variation (CV)0.45104274
Kurtosis7.6159278
Mean225974.12
Median Absolute Deviation (MAD)68000
Skewness1.4128575
Sum7.308003 × 108
Variance1.0388499 × 1010
MonotonicityNot monotonic
2025-02-16T15:03:29.470625image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 151
 
2.4%
200000 115
 
1.9%
250000 84
 
1.4%
270000 54
 
0.9%
280000 51
 
0.8%
180000 49
 
0.8%
220000 48
 
0.8%
290000 48
 
0.8%
230000 48
 
0.8%
240000 46
 
0.7%
Other values (659) 2540
41.1%
(Missing) 2944
47.7%
ValueCountFrequency (%)
11000 1
< 0.1%
11500 1
< 0.1%
14000 1
< 0.1%
15000 1
< 0.1%
18000 2
< 0.1%
19000 1
< 0.1%
24000 1
< 0.1%
26000 1
< 0.1%
28700 1
< 0.1%
33000 1
< 0.1%
ValueCountFrequency (%)
1000000 3
< 0.1%
999999 4
0.1%
826000 1
 
< 0.1%
782000 1
 
< 0.1%
720000 1
 
< 0.1%
700000 2
< 0.1%
678167 1
 
< 0.1%
657000 1
 
< 0.1%
600000 2
< 0.1%
580000 1
 
< 0.1%

contact
Text

Distinct1201
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size625.8 KiB
2025-02-16T15:03:30.402876image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length82
Median length27
Mean length6.2393979
Min length1

Characters and Unicode

Total characters38547
Distinct characters141
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique773 ?
Unique (%)12.5%

Sample

1st rowToyota
2nd rowCaddy
3rd rowToyota
4th rowРыбница
5th rowРыбница
ValueCountFrequency (%)
usauto 417
 
6.7%
александр 348
 
5.6%
сергей 312
 
5.1%
олег 185
 
3.0%
андрей 184
 
3.0%
дмитрий 180
 
2.9%
игорь 172
 
2.8%
евгений 122
 
2.0%
владимир 116
 
1.9%
вадим 109
 
1.8%
Other values (1086) 4033
65.3%
2025-02-16T15:03:31.746139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
а 2716
 
7.0%
и 2678
 
6.9%
е 2267
 
5.9%
р 2158
 
5.6%
л 1852
 
4.8%
н 1702
 
4.4%
7 1592
 
4.1%
й 1368
 
3.5%
с 1103
 
2.9%
д 1071
 
2.8%
Other values (131) 20040
52.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27032
70.1%
Uppercase Letter 5910
 
15.3%
Decimal Number 5305
 
13.8%
Other Punctuation 163
 
0.4%
Math Symbol 71
 
0.2%
Dash Punctuation 34
 
0.1%
Close Punctuation 13
 
< 0.1%
Currency Symbol 8
 
< 0.1%
Other Number 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
а 2716
 
10.0%
и 2678
 
9.9%
е 2267
 
8.4%
р 2158
 
8.0%
л 1852
 
6.9%
н 1702
 
6.3%
й 1368
 
5.1%
с 1103
 
4.1%
д 1071
 
4.0%
т 927
 
3.4%
Other values (48) 9190
34.0%
Uppercase Letter
ValueCountFrequency (%)
А 875
14.8%
В 718
 
12.1%
С 504
 
8.5%
Д 376
 
6.4%
И 364
 
6.2%
A 307
 
5.2%
S 264
 
4.5%
М 242
 
4.1%
U 227
 
3.8%
О 226
 
3.8%
Other values (42) 1807
30.6%
Other Punctuation
ValueCountFrequency (%)
. 116
71.2%
* 21
 
12.9%
, 9
 
5.5%
! 4
 
2.5%
/ 4
 
2.5%
@ 3
 
1.8%
% 2
 
1.2%
: 1
 
0.6%
? 1
 
0.6%
& 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
7 1592
30.0%
0 634
 
12.0%
1 477
 
9.0%
3 428
 
8.1%
8 415
 
7.8%
5 398
 
7.5%
2 383
 
7.2%
9 361
 
6.8%
6 333
 
6.3%
4 284
 
5.4%
Math Symbol
ValueCountFrequency (%)
+ 69
97.2%
= 2
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 31
91.2%
— 3
 
8.8%
Currency Symbol
ValueCountFrequency (%)
₽ 5
62.5%
$ 3
37.5%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Number
ValueCountFrequency (%)
⁰ 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Cyrillic 27617
71.6%
Common 5605
 
14.5%
Latin 5325
 
13.8%

Most frequent character per script

Cyrillic
ValueCountFrequency (%)
а 2716
 
9.8%
и 2678
 
9.7%
е 2267
 
8.2%
р 2158
 
7.8%
л 1852
 
6.7%
н 1702
 
6.2%
й 1368
 
5.0%
с 1103
 
4.0%
д 1071
 
3.9%
т 927
 
3.4%
Other values (49) 9775
35.4%
Latin
ValueCountFrequency (%)
u 667
12.5%
o 564
 
10.6%
t 522
 
9.8%
a 484
 
9.1%
A 307
 
5.8%
s 296
 
5.6%
S 264
 
5.0%
U 227
 
4.3%
i 226
 
4.2%
e 215
 
4.0%
Other values (41) 1553
29.2%
Common
ValueCountFrequency (%)
7 1592
28.4%
0 634
 
11.3%
1 477
 
8.5%
3 428
 
7.6%
8 415
 
7.4%
5 398
 
7.1%
2 383
 
6.8%
9 361
 
6.4%
6 333
 
5.9%
4 284
 
5.1%
Other values (21) 300
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Cyrillic 27617
71.6%
ASCII 10918
 
28.3%
Currency Symbols 5
 
< 0.1%
None 4
 
< 0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

Cyrillic
ValueCountFrequency (%)
а 2716
 
9.8%
и 2678
 
9.7%
е 2267
 
8.2%
р 2158
 
7.8%
л 1852
 
6.7%
н 1702
 
6.2%
й 1368
 
5.0%
с 1103
 
4.0%
д 1071
 
3.9%
т 927
 
3.4%
Other values (49) 9775
35.4%
ASCII
ValueCountFrequency (%)
7 1592
 
14.6%
u 667
 
6.1%
0 634
 
5.8%
o 564
 
5.2%
t 522
 
4.8%
a 484
 
4.4%
1 477
 
4.4%
3 428
 
3.9%
8 415
 
3.8%
5 398
 
3.6%
Other values (69) 4737
43.4%
Currency Symbols
ValueCountFrequency (%)
₽ 5
100.0%
None
ValueCountFrequency (%)
⁰ 4
100.0%
Punctuation
ValueCountFrequency (%)
— 3
100.0%

fone
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size440.2 KiB

date_notice
Date

Distinct6051
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size96.5 KiB
Minimum2022-12-05 15:30:00
Maximum2025-01-28 21:32:00
2025-02-16T15:03:32.116249image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:32.486179image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

manth
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size96.5 KiB

model
Text

Distinct572
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size431.9 KiB
2025-02-16T15:03:33.485951image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length6.4878601
Min length1

Characters and Unicode

Total characters40082
Distinct characters92
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)2.9%

Sample

1st rowAvensis
2nd rowCaddy
3rd rowPrius
4th row5er 520
5th rowGX
ValueCountFrequency (%)
passat 331
 
3.9%
rx 328
 
3.9%
e 231
 
2.7%
e-klasse 227
 
2.7%
avensis 199
 
2.4%
5er 174
 
2.1%
prius 172
 
2.0%
camry 169
 
2.0%
450h 165
 
2.0%
golf 158
 
1.9%
Other values (550) 6294
74.5%
2025-02-16T15:03:34.877361image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3737
 
9.3%
s 2727
 
6.8%
r 2493
 
6.2%
e 2327
 
5.8%
2270
 
5.7%
0 1851
 
4.6%
o 1580
 
3.9%
n 1451
 
3.6%
i 1444
 
3.6%
l 1263
 
3.2%
Other values (82) 18939
47.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23385
58.3%
Uppercase Letter 7728
 
19.3%
Decimal Number 6022
 
15.0%
Space Separator 2270
 
5.7%
Dash Punctuation 633
 
1.6%
Open Punctuation 15
 
< 0.1%
Close Punctuation 15
 
< 0.1%
Other Punctuation 12
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3737
16.0%
s 2727
11.7%
r 2493
10.7%
e 2327
10.0%
o 1580
 
6.8%
n 1451
 
6.2%
i 1444
 
6.2%
l 1263
 
5.4%
t 1211
 
5.2%
u 705
 
3.0%
Other values (30) 4447
19.0%
Uppercase Letter
ValueCountFrequency (%)
C 895
11.6%
A 832
10.8%
S 753
9.7%
P 691
8.9%
X 677
8.8%
E 664
8.6%
R 538
 
7.0%
V 494
 
6.4%
M 389
 
5.0%
G 330
 
4.3%
Other values (22) 1465
19.0%
Decimal Number
ValueCountFrequency (%)
0 1851
30.7%
5 947
15.7%
2 827
13.7%
3 724
 
12.0%
4 515
 
8.6%
1 384
 
6.4%
6 352
 
5.8%
7 202
 
3.4%
8 148
 
2.5%
9 72
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/ 5
41.7%
' 4
33.3%
, 1
 
8.3%
. 1
 
8.3%
& 1
 
8.3%
Space Separator
ValueCountFrequency (%)
2270
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 633
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31056
77.5%
Common 8969
 
22.4%
Cyrillic 57
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3737
 
12.0%
s 2727
 
8.8%
r 2493
 
8.0%
e 2327
 
7.5%
o 1580
 
5.1%
n 1451
 
4.7%
i 1444
 
4.6%
l 1263
 
4.1%
t 1211
 
3.9%
C 895
 
2.9%
Other values (42) 11928
38.4%
Common
ValueCountFrequency (%)
2270
25.3%
0 1851
20.6%
5 947
10.6%
2 827
 
9.2%
3 724
 
8.1%
- 633
 
7.1%
4 515
 
5.7%
1 384
 
4.3%
6 352
 
3.9%
7 202
 
2.3%
Other values (10) 264
 
2.9%
Cyrillic
ValueCountFrequency (%)
а 8
14.0%
Т 6
10.5%
С 6
10.5%
е 4
 
7.0%
я 4
 
7.0%
Д 3
 
5.3%
р 3
 
5.3%
у 3
 
5.3%
г 3
 
5.3%
в 3
 
5.3%
Other values (10) 14
24.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40025
99.9%
Cyrillic 57
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3737
 
9.3%
s 2727
 
6.8%
r 2493
 
6.2%
e 2327
 
5.8%
2270
 
5.7%
0 1851
 
4.6%
o 1580
 
3.9%
n 1451
 
3.6%
i 1444
 
3.6%
l 1263
 
3.2%
Other values (62) 18882
47.2%
Cyrillic
ValueCountFrequency (%)
а 8
14.0%
Т 6
10.5%
С 6
10.5%
е 4
 
7.0%
я 4
 
7.0%
Д 3
 
5.3%
р 3
 
5.3%
у 3
 
5.3%
г 3
 
5.3%
в 3
 
5.3%
Other values (10) 14
24.6%

len_dop_info
Real number (ℝ)

Distinct974
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245.31418
Minimum3
Maximum3915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-02-16T15:03:35.232908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q154
median151
Q3345
95-th percentile790
Maximum3915
Range3912
Interquartile range (IQR)291

Descriptive statistics

Standard deviation274.05249
Coefficient of variation (CV)1.117149
Kurtosis11.841116
Mean245.31418
Median Absolute Deviation (MAD)122
Skewness2.3205201
Sum1515551
Variance75104.765
MonotonicityNot monotonic
2025-02-16T15:03:35.674528image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 776
 
12.6%
76 33
 
0.5%
31 30
 
0.5%
25 28
 
0.5%
26 27
 
0.4%
83 26
 
0.4%
96 24
 
0.4%
93 24
 
0.4%
9 23
 
0.4%
18 23
 
0.4%
Other values (964) 5164
83.6%
ValueCountFrequency (%)
3 776
12.6%
4 5
 
0.1%
5 3
 
< 0.1%
6 9
 
0.1%
7 6
 
0.1%
8 4
 
0.1%
9 23
 
0.4%
10 4
 
0.1%
11 10
 
0.2%
12 16
 
0.3%
ValueCountFrequency (%)
3915 1
< 0.1%
3339 1
< 0.1%
2704 1
< 0.1%
2099 1
< 0.1%
1963 1
< 0.1%
1843 1
< 0.1%
1804 1
< 0.1%
1643 1
< 0.1%
1633 1
< 0.1%
1628 1
< 0.1%

mileage_orig
Real number (ℝ)

MISSING 

Distinct1067
Distinct (%)20.5%
Missing973
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean135403.51
Minimum1
Maximum1000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-02-16T15:03:36.063884image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile100
Q1260
median126000
Q3240000
95-th percentile350000
Maximum1000000
Range999999
Interquartile range (IQR)239740

Descriptive statistics

Standard deviation134965.98
Coefficient of variation (CV)0.99676869
Kurtosis1.5311103
Mean135403.51
Median Absolute Deviation (MAD)125710
Skewness0.83306404
Sum7.0477528 × 108
Variance1.8215816 × 1010
MonotonicityNot monotonic
2025-02-16T15:03:36.463982image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 146
 
2.4%
200000 110
 
1.8%
300 95
 
1.5%
250000 77
 
1.2%
1 65
 
1.1%
200 61
 
1.0%
250 51
 
0.8%
270000 51
 
0.8%
180000 48
 
0.8%
280000 48
 
0.8%
Other values (1057) 4453
72.1%
(Missing) 973
 
15.7%
ValueCountFrequency (%)
1 65
1.1%
2 5
 
0.1%
3 4
 
0.1%
4 7
 
0.1%
5 2
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
11 3
 
< 0.1%
13 1
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
1000000 3
< 0.1%
999999 4
0.1%
826000 1
 
< 0.1%
782000 1
 
< 0.1%
720000 1
 
< 0.1%
700000 2
< 0.1%
678167 1
 
< 0.1%
657000 1
 
< 0.1%
600000 2
< 0.1%
580000 1
 
< 0.1%

Interactions

2025-02-16T15:03:15.632910image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:07.451291image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:08.998082image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:10.495656image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:12.124883image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:13.661376image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
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2025-02-16T15:03:07.696183image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:09.246926image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:10.755716image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:12.361937image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:13.919436image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:16.135021image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:07.960243image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:09.485908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:11.038940image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:12.624015image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:14.182494image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:16.408082image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:08.253309image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:09.748966image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:11.317005image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
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2025-02-16T15:03:14.495564image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:16.643138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:08.500364image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:09.982066image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:11.583324image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:13.142139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:14.806651image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
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2025-02-16T15:03:10.237151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:11.886411image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:13.418228image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-02-16T15:03:15.094756image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Missing values

2025-02-16T15:03:17.329302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-16T15:03:18.227503image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-16T15:03:18.862099image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

brendvolumetip_dvigateljagodpriseclass_autobodystatedoorfueltransmissionconditioneraudiomileagecontactfonedate_noticemanthmodellen_dop_infomileage_orig
0Toyota2000.00Дизель2009.005900.00ЛегковойуниверсалОтличное4/5дизель6-тиступ.мех.климатконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)212000.00Toyota779104072025-01-28 21:32:002025-01Avensis334.00212000.00
1Volkswagen2000.00Бензин-Газ2007.006200.00ЛегковойминивенОтличное4/5бензин5-тиступ.мех.климатконтрольавтомагнитолаCD/MP3(безUSB)NaNCaddy777427942025-01-28 21:23:002025-01Caddy3.00190.00
2Toyota1800.00Гибрид2009.008999.00ЛегковойхетчбекОтличное4/5бензинавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)157000.00Toyota779895662025-01-28 21:23:002025-01Prius3.00157000.00
3BMW2000.00Бензин1997.001700.00NaNNaNХорошееNaNNaN5-тиступ.мех.климатконтрольавтомагнитолаCD/MP3(безUSB)NaNРыбница778005862025-01-28 21:07:002025-015er 52064.00NaN
4Lexus4600.00Бензин2012.0029000.00NaNNaNОтличноеNaNNaNавтоматклиматконтрольавтомагнитолаCD/MP3(безUSB)NaNРыбница778005862025-01-28 21:05:002025-01GX354.00NaN
5Mercedes-Benz3200.00Дизель2008.0010000.00ЛегковойвнедорожникХорошее4/5дизельавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)294000.00Владимир774562302025-01-28 20:52:002025-01GL-klasse GL 32018.00294000.00
6Toyota1800.00Гибрид2013.007500.00ЛегковойхетчбекОтличное4/5NaNавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)NaNРххх775332042025-01-28 20:45:002025-01Prius72.00NaN
7Ford2000.00Бензин2015.006700.00ЛегковойседанОтличное4/5бензинавтоматкондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)NaNЮрий777920302025-01-28 20:42:002025-01Focus165.00140.00
8Volkswagen1400.00Бензин-Газ2011.008100.00ЛегковойуниверсалОтличное4/5бензинавтоматклиматконтрольавтомагнитолаHi-End261000.00Василий778524322025-01-28 20:42:002025-01Passat258.00261000.00
9Lexus3500.00Бензин-Газ2009.009000.00ЛегковойвнедорожникОтличное4/5бензинавтоматклиматконтрольавтомагнитолаCD/MP3(сUSBиBluetooth)160000.00Владимир774562302025-01-28 20:38:002025-01RX 35015.00160000.00
brendvolumetip_dvigateljagodpriseclass_autobodystatedoorfueltransmissionconditioneraudiomileagecontactfonedate_noticemanthmodellen_dop_infomileage_orig
9209VolkswagenNaNБензин2010.006000.00NaNкроссоверNaNNaNNaNавтоматNaNNaNNaNгеннадий778196482022-12-07 20:00:002022-12Tiguan5.002000.00
9210Volkswagen1800.00Бензин-Газ1991.001400.00ЛегковойседанОтличное4/5газ5-тиступ.мех.кондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)123456.00Евгений779988962022-12-07 19:52:002022-12Passat23.00123456.00
9211Nissan2000.00Бензин1998.001500.00ЛегковойхетчбекХорошее4/5бензин5-тиступ.мех.кондиционеравтомагнитолаCD/MP3(безUSB)NaNИван777970362022-12-07 16:06:002022-12Primera3.00290.00
9216Toyota1995.00Дизель2005.003700.00ЛегковойуниверсалОтличное4/5дизель5-тиступ.мех.климатконтрольавтомагнитола233000.00Виктор779755832022-12-07 09:45:002022-12Corolla161.00233000.00
9217Toyota2000.00Дизель2001.002500.00ЛегковойуниверсалХорошее4/5дизель6-тиступ.мех.NaNNaNNaNАлександр777808022022-12-06 12:11:002022-12Avensis21.00271.00
9218Toyota2000.00Дизель2004.002600.00ЛегковойуниверсалNaN4/5дизель5-тиступ.мех.кондиционерNaNNaNЕвгений777945232022-12-05 20:30:002022-12Corolla162.00NaN
9219Mercedes-Benz3200.00Дизель2004.005800.00ЛегковойуниверсалОтличноеNaNдизельавтоматклиматконтрольNaN293000.00Александр777992322022-12-05 19:45:002022-12E-klasse E 32018.00293000.00
9220Volkswagen1900.00Дизель2006.005300.00ЛегковойхетчбекХорошее4/5дизель6-тиступ.мех.кондиционеравтомагнитола175645.00Владимир777610102022-12-05 15:55:002022-12Golf Plus91.00175645.00
9221Toyota2000.00Дизель2006.004500.00ЛегковойуниверсалОтличное4/5дизель6-тиступ.мех.кондиционеравтомагнитола213456.00Владимир777610102022-12-05 15:39:002022-12Avensis109.00213456.00
9222Toyota2000.00Дизель2005.005500.00ЛегковойминивенОтличное4/5дизель6-тиступ.мех.климатконтрольавтомагнитола212443.00Владимир777610102022-12-05 15:30:002022-12Avensis Verso140.00212443.00

Duplicate rows

Most frequently occurring

brendvolumetip_dvigateljagodpriseclass_autobodystatedoorfueltransmissionconditioneraudiomileagecontactdate_noticemodellen_dop_infomileage_orig# duplicates
1Mitsubishi1700.00Бензин-Газ1994.001150.00ЛегковойседанУдовлетворительное4/5газ5-тиступ.мех.безкондиционераавтомагнитола552300.00Дмитрий2024-08-10 22:46:00Galant3.00552300.003
0Audi2000.00Бензин1992.001600.00ЛегковойседанОтличное4/5бензин5-тиступ.мех.кондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)NaN0775281762023-04-10 14:14:0080456.00NaN2
2Toyota2000.00Дизель2006.004500.00ЛегковойNaNХорошее4/5дизель6-тиступ.мех.климатконтрольавтомагнитолаNaNВиталик2023-03-06 20:36:00Avensis543.00300.002
3ToyotaNaNГибрид2010.008500.00ЛегковойхетчбекХорошее4/5бензинроботизированаякондиционеравтомагнитолаCD/MP3(сUSBиBluetooth)NaN+373778627262023-01-06 17:17:00Prius168.00185.002